Snow and Mountain Hydrology

Snow cover duration, peak snow accumulations, snowmelt timing and snowmelt rates are some of the factors associated with the water cycle in mountain environments, with strong ecological and socio-economical impacts, not only in Switzerland, but in other mountain environments across the globe. Currently, we are performing research in these areas combining terrestrial laser scanning (TLS, see Figure 3), in-situ energy balance stations, wireless sensor networks, and other instrumentation. The overarching objective of this research is to better understand the dominant processes controlling the spatial features of snow accumulation and melt in alpine environments in the Swiss Alps.

Figure 1 – Terrestrial laser scanning (TLS) is performed in order to analyse the snow cover melting on large areas with high precision.

Our efforts are concentrated in Val Ferret, located in the Swiss canton of Valais. The watershed is an alpine valley draining into the Dranse de Ferret, the Dranse, and eventually the Rhone. A map with the localisation of the meteorological stations, cameras and gauging stations is shown on Figure 2.

Figure 2 – Localization of meteorological stations, gauging stations and cameras in the analysed watershed in Val Ferret, Switzerland.

Streamflow measurements are performed for a drainage area of around 20 km2, with an elevation range between 1775 m and 3206 m, and with a mean elevation of 2423 m. The slopes are moderate to steep (mean 31.6 degrees, maximum 88.9 degrees) and vegetation is mainly grassland with some patches of firs and larch at lower elevations. The spring and summer hydrologic cycle has been the topic of extensive research in the Environmental Fluid Mechanics Laboratory of EPFL (EFLUM).

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Figure 3 – Terrestrial laser scanner used to measure the spatial distribution of snow in Val Ferret in order to estimate local and global snowmelt rates

Terrestrial Laser Scanning is being performed to assess the spatial distribution of snowmelt in portions of the catchment (see Figure 3). By performing repeated laser scans of the snow covered topography, the difference in surface elevations can be used to determine the change in snow depth at very high horizontal and vertical resolutions (of the order of centimeters to tens of centimeters). From this, mass changes can be estimated and analyzed to study differential melting patterns, together with the processes affecting them. This information is useful to better understand the processes driving the melting, improve modeling strategies at such spatial resolutions, and compare model results to the observations of this differential melt. Sample laser scans in the basin is shown in the Figure 4.

Figure 4 – Typical view of laser scanned data. Location: Val Ferret, Switzerland

Additional data is being obtained from meteorological stations distributed along the basin.
(see Figure 5).  These meteorological stations are part of an autonomous, self-organizing, multi-hop wireless sensor network (link to Sensorscope here) and stations include sensors to measure solar radiation, wind speed and direction, air and surface temperature, humidity, soil moisture and temperature, matrix potential, and precipitation

Figure 5 – Installation of meteorological stations

These datasets are complemented with a series of  autonomous, low power time lapse photography cameras located at high points in the watershed (see Figure 6).

Figure 6 – Camera station maintenance

The projection of these image data onto the topographic surface and color-based classification between snow and non-snow surfaces allows us to determine the development of bare ground areas as snowmelt progresses. This is not only important for snow mass balance estimation, but also for albedo change and energy dynamics that are important for hydrological purposes.

Ultimately, these datasets are allowing us to develop a better understanding of snowmelt processes in alpine environments, focusing on the influence of geomorphological and climatological characteristics of the watershed (e.g., elevation, slope, aspect, solar radiation, temperature) on the spatial and temporal patterns of snowmelt.